It is a fundamental challenge to understand how the function of a network is related to its
structural organization. Adaptive dynamical networks represent a broad class of systems that …

Moment closure methods appear in myriad scientific disciplines in the modelling of complex
systems. The goal is to achieve a closed form of a large, usually even infinite, set of coupled …

Over the past decade, the use of networks has led to a new modelling paradigm combining
several branches of science, including physics, mathematics, biology and social sciences …

Mean-field deterministic epidemic models have been successful in uncovering several
important dynamic properties of stochastic epidemic spreading processes over complex …

A wide class of binary-state dynamics on networks—including, for example, the voter model,
the Bass diffusion model, and threshold models—can be described in terms of transition …

Epidemic containment is a major concern when confronting large-scale infections in
complex networks. Many studies have been devoted to analytically understand how to …

A stochastic model for the spread of an SIS epidemic among a population consisting of N
individuals, each having heterogeneous infectiousness and/or susceptibility, is considered …

In this paper a random link activation–deletion (RLAD) model is proposed that gives rise to a
stochastically evolving network. This dynamic network is then coupled to a simple …

We consider Markovian susceptible-infectious-removed (SIR) dynamics on time-invariant
weighted contact networks where the infection and removal processes are Poisson and …

Higher-order interactions play an important role in complex contagion processes. Mean-field
approximations have been used to characterize the onset of spreading in the presence of …